Real-Time Multimodal Activity-Aware Error Detection in Robot-Assisted Surgery
Robot-assisted minimally invasive surgery improves surgical precision but introduces complexity, making technical error detection essential for ensuring patient safety. Current executional error detection methods using video data often overlook fine-grained contextual descriptions of activities and error types within the hierarchical structure of surgical procedures. They also under-utilize complementary multimodal information. We propose a unified framework for executional error detection that leverages multimodal input, including video, kinematics, and descriptive textual prompts. Through activity prompting, we integrate descriptive language in gesture-level activities, instrument-objec...
| Authors | Seyed Hamid Reza Roodabeh, Zongyu Li, Homa Alemzadeh |
|---|---|
| Primary category | cs.RO |
| Published | 22 June 2026 |
| Last updated at source | 22 June 2026 |
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